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» Online Algorithms for Mining Semi-structured Data Stream
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EDBT
2004
ACM
110views Database» more  EDBT 2004»
16 years 1 months ago
Using Convolution to Mine Obscure Periodic Patterns in One Pass
The mining of periodic patterns in time series databases is an interesting data mining problem that can be envisioned as a tool for forecasting and predicting the future behavior o...
Mohamed G. Elfeky, Walid G. Aref, Ahmed K. Elmagar...
SAC
2009
ACM
15 years 8 months ago
Evaluating algorithms that learn from data streams
In the past years, the theory and practice of machine learning and data mining have been focused on static and finite data sets from where learning algorithms generate a static m...
João Gama, Pedro Pereira Rodrigues, Raquel ...
JMLR
2010
130views more  JMLR 2010»
14 years 8 months ago
MOA: Massive Online Analysis, a Framework for Stream Classification and Clustering
Massive Online Analysis (MOA) is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA is designed to deal...
Albert Bifet, Geoff Holmes, Bernhard Pfahringer, P...
VLDB
2006
ACM
190views Database» more  VLDB 2006»
16 years 1 months ago
Online summarization of dynamic time series data
Managing large-scale time series databases has attracted significant attention in the database community recently. Related fundamental problems such as dimensionality reduction, tr...
Ümit Y. Ogras, Hakan Ferhatosmanoglu

Publication
309views
17 years 1 months ago
SOLE: Scalable On-Line Execution of Continuous Queries on Spatio-temporal Data Streams
This paper presents the Scalable On-Line Execution algorithm (SOLE, for short) for continuous and on-line evaluation of concurrent continuous spatio- temporal queries over data str...
Mohamed F. Mokbel, Walid G. Aref